Time-based storage within a dispersed storage network

ABSTRACT

A method begins by a dispersed storage (DS) processing obtaining estimated future availability information for storage units and organizing a plurality of sets of encoded data slices into a plurality of group-sets of encoded data slices. For each of the plurality of group-sets of encoded data slices, the method continues with the DS processing module estimating an approximate storage completion time to produce a plurality of approximate storage completion times. The method continues with the DS processing module establishing a time-availability pattern for writing the plurality of group-sets of encoded data slices to the storage units based on the estimated future availability information and the plurality of approximate storage completion times. The method continues with the DS processing module sending the plurality of group-sets of encoded data slices to at least some of the storage units for storage therein in accordance with the time-availability pattern.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 61/860,498,entitled “DISPERSED STORAGE AND COMPUTING NETWORK COMPONENTS ANDOPTIMIZATIONS”, filed Jul. 31, 2013, which is hereby incorporated hereinby reference in its entirety and made part of the present U.S. UtilityPatent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

NOT APPLICABLE

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC—NOTAPPLICABLE BACKGROUND

1. Technical Field

This present disclosure relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present disclosure;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present disclosure;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present disclosure;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent disclosure;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present disclosure;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present disclosure;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present disclosure;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent disclosure;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present disclosure;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present disclosure;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present disclosure;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present disclosure;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent disclosure;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present disclosure;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present disclosure;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present disclosure;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent disclosure;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present disclosure;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present disclosure;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present disclosure;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present disclosure;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentdisclosure;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present disclosure;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentdisclosure;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present disclosure;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentdisclosure;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentdisclosure;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent disclosure;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present disclosure;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentdisclosure;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentdisclosure;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present disclosure;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present disclosure;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentdisclosure;

FIGS. 40A-40D are schematic block diagrams of an embodiment of adispersed storage network (DSN) illustrating an example of storing datain DSN memory in accordance with the present disclosure;

FIG. 40E is a flowchart illustrating an example of accessing data inaccordance with the present disclosure;

FIG. 41 is a flowchart illustrating an example of updating a dispersedstorage network (DSN) address in accordance with the present disclosure;

FIG. 42 is a flowchart illustrating an example of accessing an encodeddata slice in accordance with the present disclosure;

FIGS. 43A, 43C-F are schematic block diagrams of an embodiment of adispersed storage network (DSN) illustrating an example of time-basedstorage of data in accordance with the present disclosure;

FIG. 43B is a timing diagram illustrating an example of generating atime-availability pattern in accordance with the present disclosure;

FIG. 43G is a flowchart illustrating an example of time-based storage ofdata in accordance with the present disclosure;

FIG. 44A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit in accordance with thepresent disclosure;

FIG. 44B is a flowchart illustrating an example of assigning resourcesin accordance with the present disclosure;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentdisclosure;

FIG. 45B is a diagram illustrating an example of load-balancing inaccordance with the present disclosure;

FIG. 46A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit in accordance with thepresent disclosure;

FIG. 46B is a diagram illustrating an example of memory utilization inaccordance with the present disclosure;

FIG. 46C is a diagram illustrating another example of memory utilizationin accordance with the present disclosure;

FIG. 46D is a flowchart illustrating an example of updating memoryutilization information in accordance with the present disclosure;

FIG. 46E is a flowchart illustrating example ways to identify slicesneeding a rebuild in accordance with the present disclosure;

FIG. 46F is a flowchart illustrating another example of updating memoryutilization information;

FIG. 46G is a schematic block diagram illustrating an example DST clientmodule structure for memory utilization;

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentdisclosure;

FIG. 47B is a diagram illustrating an example of generating a slice namein accordance with the present disclosure;

FIG. 47C is a flowchart illustrating an example of co-locating storageof data in accordance with the present disclosure;

FIG. 47D is a flowchart illustrating one example of obtaining theplurality of sets of encoded data slices to be co-located; and

FIG. 47E is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentdisclosure.

DETAILED DESCRIPTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generateper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations include authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ (e.g., corrupted) or missing encoded data slices. Ata high level, the DST integrity processing unit 20 performs rebuildingby periodically attempting to retrieve/list encoded data slices, and/orslice names of the encoded data slices, from the DSTN module 22. Forretrieved encoded slices, they are checked for errors due to datacorruption, outdated version, etc. If a slice includes an error, it isflagged as a ‘bad’ slice. For encoded data slices that were not receivedand/or not listed, they are flagged as missing slices. Bad and/ormissing slices are subsequently rebuilt using other retrieved encodeddata slices that are deemed to be good slices to produce rebuilt slices.The rebuilt slices are stored in memory of the DSTN module 22. Note thatthe DST integrity processing unit 20 may be a separate unit as shown, itmay be included in the DSTN module 22, and it may be included in the DSTprocessing unit 16, and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the I0 device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks). With the data blocks arranged into the desired sequentialorder, they are divided into data segments based on the segmentinginformation. In this example, the data partition is divided into 8 datasegments; the first 7 include 2 columns of three rows and the lastincludes 1 column of three rows. Note that the first row of the 8 datasegments is in sequential order of the first 15 data blocks; the secondrow of the 8 data segments in sequential order of the second 15 datablocks; and the third row of the 8 data segments in sequential order ofthe last 15 data blocks. Note that the number of data blocks, thegrouping of the data blocks into segments, and size of the data blocksmay vary to accommodate the desired distributed task processingfunction.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first—third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the second set of encoded data slices includes errorcorrection data based on the first—third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth DST execution unit;and the fifth slice grouping of the second data partition (e.g., slicegroup 2_5, which includes second error coding information) is sent tothe first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions. The DSTclient module 34 receives DST feedback 168 (e.g., sub-partial results),via the interface 169, from the DST execution units to which the taskwas offloaded. The DST client module 34 provides the sub-partial resultsto the DST execution unit, which processes the sub-partial results toproduce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, and partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186.

The slice security information includes data decompression, decryption,de-watermarking, integrity check (e.g., CRC verification, etc.), and/orany other type of digital security. For example, when the inverse perslice security processing module 202 is enabled, it verifies integrityinformation (e.g., a CRC value) of each encoded data slice 122, itdecrypts each verified encoded data slice, and decompresses eachdecrypted encoded data slice to produce slice encoded data 158. When theinverse per slice security processing module 202 is not enabled, itpasses the encoded data slices 122 as the sliced encoded data 158 or isbypassed such that the retrieved encoded data slices 122 are provided asthe sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section.

The DS error decoding module 182 includes an inverse per slice securityprocessing module 202, a de-slicing module 204, an error decoding module206, an inverse segment security module 208, and a de-segmentingprocessing module 210. The dispersed error decoding module 182 isoperable to de-slice and decode encoded slices per data segment 218utilizing a de-slicing and decoding function 228 to produce a pluralityof data segments that are de-segmented utilizing a de-segment function230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task⇄sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1;and SLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., 3/5 for the first data entry), segment security information(e.g., SEG_1), per slice security information (e.g., SLC_1), and/or anyother information regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of 3/5; SEG_2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task⇄sub-task mapping information table 246 includes a task field256 and a sub-task field 258. The task field 256 identifies a taskstored in the memory of a distributed storage and task network (DSTN)module and the corresponding sub-task fields 258 indicates whether thetask includes sub-tasks and, if so, how many and if any of the sub-tasksare ordered. In this example, the task⇄sub-task mapping informationtable 246 includes an entry for each task stored in memory of the DSTNmodule (e.g., task 1 through task k). In particular, this exampleindicates that task 1 includes 7 sub-tasks; task 2 does not includesub-tasks, and task k includes r number of sub-tasks (where r is aninteger greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1-identifynon-words (non-ordered); task 1_2-identify unique words (non-ordered);task 1_3-translate (non-ordered); task 1_4 -translate back (orderedafter task 1_3); task 1_5—compare to ID errors (ordered after task 1-4);task 1_6—determine non-word translation errors (ordered after task 1_5and 1_1); and task 1_7-determine correct translations (ordered after 1_5and 1_2). The sub-task further indicates whether they are an orderedtask (i.e., are dependent on the outcome of another task) or non-order(i.e., are independent of the outcome of another task). Task 2 does notinclude sub-tasks and task 3 includes two sub-tasks: task 3_1 translate;and task 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_4) into the language of the original data toproduce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task 1_5)310 is ordered after the translation 306 and re-translation tasks 308(e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30.

As shown, DS encoded data 2 is stored as encoded data slices across thememory (e.g., stored in memories 88) of DST execution units 1-5; the DSencoded task code 1 (of task 1) and DS encoded task 3 are stored asencoded task slices across the memory of DST execution units 1-5; and DSencoded task code 2 (of task 2) is stored as encoded task slices acrossthe memory of DST execution units 3-7. As indicated in the data storageinformation table and the task storage information table of FIG. 29, therespective data/task has DS parameters of 3/5 for their decodethreshold/pillar width; hence spanning the memory of five DST executionunits.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2_z by DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1, 4_1, and5_1 search for non-words in data partitions 2_1 through 2_z to producetask 1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution informationas task 1_1 to produce task 1_2 intermediate results (R1-2, which is thelist of unique words).

Task 1_3 (e.g., translate) includes task execution information as beingnon-ordered (i.e., is independent), having DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1 through 2_4 andhaving DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2 translate datapartitions 2_5 through 2_z to produce task 1_3 intermediate results(R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1_3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3_z to produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task 1_5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2_z) with partitions of task 1-4 intermediate results partitionsR1-4_1 through R1-4 _(—)z to produce task 1_5 intermediate results(R1-5, which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors dueto non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctlytranslated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2_z by DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2_z to produce task 2 intermediate results (R2,which is a list of specific words and/or phrases).

Task 3_2 (e.g., find specific translated words and/or phrases) isordered after task 1_3 (e.g., translate) is to be performed onpartitions R1-3_1 through R1-3_z by DT execution modules 1_2, 2_2, 3_2,4_2, and 5_2. For instance, DT execution modules 1_2, 2_2, 3_2, 4_2, and5_2 search for specific translated words and/or phrases in thepartitions of the translated data (R1-3_1 through R1-3_z) to producetask 3_2 intermediate results (R3-2, which is a list of specifictranslated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32) executes task 1_1 to produce a secondpartial result 102 of non-words found in the second data partition. Thesets of DT execution modules (as per the DST allocation information)perform task 1_1 on the data partitions until the “z” set of DTexecution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1_m). If the first intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1 ^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_2 to produce the second intermediate result (R1-2), whichis a list of unique words found in the data 92. The processing module ofDST execution 1 is engaged to aggregate the first through “zth” partialresults of unique words to produce the second intermediate result. Theprocessing module stores the second intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2_m). If the second intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2_z). For the data partitions, theallocated set of DT execution modules 90 executes task 1_3 to producepartial results 102 (e.g., 1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3_y). For each partition of the third intermediate result,the DST client module uses the DS error encoding parameters of the data(e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_5 to produce the fifth intermediate result (R1-5), which is thelist of incorrectly translated words and/or phrases. In particular, theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of the list of incorrectly translatedwords and/or phrases to produce the fifth intermediate result. Theprocessing module stores the fifth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5_z). Foreach partition of the fifth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_6 to produce the sixth intermediate result (R1-6), which is thelist of incorrectly translated words and/or phrases due to non-words. Inparticular, the processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases due to non-words to producethe sixth intermediate result. The processing module stores the sixthintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6_z).

For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_7 to produce the seventh intermediate result (R1-7), which is thelist of correctly translated words and/or phrases. In particular, theprocessing module of DST execution 3 is engaged to aggregate the firstthrough “zth” partial results of the list of correctly translated wordsand/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabytes). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIGS. 40A-40D are schematic block diagrams of an embodiment of adispersed storage network (DSN) illustrating an example of storing datain DSN memory. The DSN includes the distributed storage and task (DST)client module 34 of FIG. 1, the network 24 of FIG. 1, and thedistributed storage and task network (DSTN) module 22 of FIG. 1.Hereafter, the DSTN module 22 may be referred to interchangeably as theDSN memory. The DSTN module 22 includes one or more storage generations,where each storage generation is associated with a vault of the DSN. Avault includes virtual storage of the DSN and may be associated with oneor more users of the DSN. Incremental storage generations may be addedover time to provide incremental storage capacity as a total amount ofdata stored associated with the vault grows. For example, the DSTNmodule 22 includes storage generations 1-3 during a first timeframe(e.g., as illustrated in FIGS. 40A-B) and includes storage generations1-5 during a second timeframe (e.g., as illustrated in FIGS. 40C-D).Each storage generation includes a set of DST execution (EX) units 1-n.Each DST execution unit may be implemented utilizing the DST executionunit 36 of FIG. 1. Hereafter, the DST execution unit may be referred tointerchangeably as a storage unit of a set of storage units associatedwith each storage generation.

The DST client module 34 includes the outbound DST processing 80 of FIG.3, the inbound DST processing 82 of FIG. 3, and a slice name module 350.The slice name module 350 may be implemented utilizing the processingmodule 84 of FIG. 3. The DST client module 34 further includes adispersed storage (DS) module 351. The DS module 351 may be implementedutilizing a plurality of processing modules. For instance, the pluralityof processing modules may include the processing module 84 of FIG. 3. Asa specific example, the plurality of processing module includes a firstmodule, a second module, a third module, a fourth module, a fifthmodule, and a sixth module. The first through sixth modules may beutilized to implement the outbound DST processing 80, the inbound DSTprocessing 82, and the slice name module 350. The DSN functions toaccess data 352 in the DSTN module 22 without utilizing a directory. Theaccessing of the data 352 includes storing of the data 352 andretrieving stored data to reproduce the data 352.

FIG. 40A illustrates initial steps of an example of the storing of thedata 352, where the outbound DST processing 80 receives the data 352 forstorage, where the data has a data name. The data name includes filesystem information. The file system information includes one or more ofa user identifier (ID), a vault identifier, and a file system path namefor the data. Having received the data 352, the outbound DST processing80 dispersed storage error encodes the data 352 to produce a pluralityof sets of encoded data slices.

Having produced the plurality of sets of encoded data slices, theoutbound DST processing 80 generates a plurality of sets of DSN dataaddresses based on a data object number associated with the data anddata storage information. Each set of the plurality of sets of DSN dataaddresses includes a set of DSN addresses, where the set of DSNaddresses includes a set of slice names. Each slice name includes one ormore of a slice index corresponding to a particular slice of the set ofencoded data slices, a vault ID corresponding to an associated vault, ageneration number corresponding to one of the storage generations, thedata object number, and a segment number corresponding to the set ofencoded data slices. As a specific example, the outbound DST processing80 utilizes a pseudo random number generator to produce the data objectnumber, performs a system registry lookup to retrieve the vault IDcorresponding to a requesting entity, and selects a storage generationof the storage generations to produce the generation number.

The selecting of the storage generation for storing of the data 352includes at least one of a random selection, selecting a most recentlyactivated storage generation, selecting a storage generation associatedwith a highest storage availability level, selecting a storagegeneration based on interpreting a data storage request, selecting astorage generation based on interpreting a system registry entry, andselecting a storage generation associated with a storage availabilitylevel that is greater than a storage availability threshold level. Forinstance, the outbound DST processing 80 selects a most recentlyactivated storage generation 3 as the selected storage generation toproduce generation number 3.

The data storage information includes dispersed storage error encodingparameters. The dispersed storage error encoding parameters includes oneor more of data segmenting information regarding segmenting the data 352into a plurality of data segments, a total number of encoded data slicesper set of encoded data slices, a decode threshold number of encodeddata slices per set of encoded data slices, a read threshold number ofencoded data slices per set of encoded data slices, and a writethreshold number of encoded data slices per the set of encoded dataslices. The outbound DST processing 80 determines the data storageinformation. The determining includes at least one of performing asystem registry lookup, receiving the dispersed storage error encodingparameters, and determining the dispersed storage error encodingparameters based on one or more of received storage requirements and anestimated DSN performance level.

Having generated the plurality of sets of DSN data addresses, theoutbound DST processing 80 sends, via the network 24, the plurality ofsets of encoded data slices to the DSTN module 22 (e.g., DSN memory) forstorage in accordance with the plurality of sets of DSN data addresses.As a specific example, the outbound DST processing 80 generates a set ofwrite slice requests that includes the plurality of sets of encoded dataslices and the plurality of sets of DSN data addresses, and outputs theset of write slice requests that includes the plurality of sets ofencoded data slices (EDS) 1-n of generation 3 to the set of DSTexecution units 1-n of the storage generation 3.

FIG. 40B illustrates final steps of the example of the storing of thedata 352, where the outbound DST processing 80 generates retrieval datathat is based on the data object number and the data storageinformation. As a specific example, the outbound DST processing 80aggregates the data object number, the vault ID and the generationnumber to produce the retrieval data. Having generated the retrievaldata, the outbound DST processing 80 dispersed storage error encodes theretrieval data to produce a set of encoded retrieval data slices.

With the set of encoded retrieval data slices produced, the slice namemodule 350 generates a set of DSN retrieval data addresses 356 based onthe data name 354 and on retrieval data storage information. The set ofDSN retrieval data addresses 356 includes a set of slice names for theset of encoded retrieval data slices. Each slice name for acorresponding encoded retrieval data slice includes one or more of aslice index corresponding to a particular slice of the set of encodedretrieval data slices, the vault ID, a generation number for theretrieval data corresponding to at least one of the storage generations,a retrieval data object number, and a segment number corresponding tothe set of encoded retrieval data slices. As a specific example, slicename module 350 performs a deterministic function on the data name 354to produce the retrieval data object number, and selects at least onestorage generation of the storage generations to produce the generationnumber. The deterministic function includes one or more of a hashingfunction, a hash-based message authentication code function, a maskgenerating function, and a sponge function. For instance, the slice namemodule 350 performs the mask generating function on the data name 354 todirectly produce the retrieval data object number.

The selecting of the at least one storage generation for storing of theretrieval data includes at least one of a random selection, applying adeterministic function to the data name 354, selecting the most recentlyactivated storage generation, selecting the storage generationassociated with the highest storage availability level, selecting thestorage generation based on interpreting the data storage request,selecting the storage generation based on interpreting the systemregistry entry, and selecting the storage generation associated with thestorage availability level that is greater than the storage availabilitythreshold level. For instance, the slice name module 350 performs thehashing function on the data name 354 to produce an intermediate result,and takes the intermediate result modulo number of current storagegenerations to produce generation number 2.

The retrieval data storage information includes dispersed storage errorencoding parameters for the retrieval data. The dispersed storage errorencoding parameters for the retrieval data includes one or more of atotal number of encoded retrieval data slices for the set of encodedretrieval data slices, a decode threshold number of encoded retrievaldata slices for the set of encoded retrieval data slices, a readthreshold number of encoded retrieval data slices for the set of encodedretrieval data slices, and a write threshold number of encoded retrievaldata slices for the set of encoded retrieval data slices. The outboundDST processing 80 determines the retrieval data storage information.Alternatively, the slice name module 350 determines the retrieval datastorage information. The determining includes at least one of performinga system registry lookup, receiving the dispersed storage error encodingparameters for the retrieval data, utilizing the dispersed storage errorencoding parameters of the data 352, and determining the dispersedstorage error encoding parameters for the retrieval data based on one ormore of further received storage requirements and the estimated DSNperformance level.

With the DSN retrieval data addresses 356 produced, the outbound DSTprocessing 80 sends, via the network 24, the set of encoded retrievaldata slices to the DSTN module 22 (e.g.,

DSN memory) for storage in accordance with the set of DSN retrieval dataaddresses 356. As a specific example, the outbound DST processing 80generates another set of write slice requests that includes the set ofencoded retrieval data slices and the set of DSN retrieval dataaddresses 356; and outputs the other set of write slice requests thatincludes the set of encoded retrieval data slices (ERDS) 1-n ofgeneration 2 to the set of DST execution units 1-n of the storagegeneration 2.

Alternatively, or in addition to, one or more of the slice name module350 and the outbound DST processing 80 may determine to store theretrieval data in at least one other storage generation. As a specificexample, the slice name module 350 determines to store multiple copiesof the set of encoded retrieval data slices and identifies multiple setsof storage units of the DSN memory for storing the multiple copies. Themultiple sets of storage units being part of a logical storage vaultwithin the DSN memory, where a first set of storage units of the set ofstorage units corresponds to a first generation of the DSN memory and asecond set of storage units of the set of storage units corresponds to asecond generation of the DSN memory. The determining includes one ormore of detecting that a size of the retrieval data is less than a sizethreshold level, detecting that an available storage capacity level isgreater than an available storage capacity threshold level, interpretinga system registry entry, and interpreting a request.

When determining to store multiple copies of the set of encodedretrieval data slices, the slice name module 350 generates a unique setof DSN retrieval data addresses based on the data name, on the retrievaldata storage information, and on a corresponding one of the multiplesets of storage units. As a specific example, the slice name module 350generates another set of DSN retrieval data addresses that includesgeneration 3 when identifying storage generation 3. With the other setof DSN retrieval data addresses, the outbound DST processing 80 sends,via the network 24, the set of encoded retrieval data slices to thecorresponding one of the multiple sets of storage units for storage inaccordance with the other set of DSN retrieval data addresses. As aspecific example, the outbound DST processing 80 generates yet anotherset of write slice requests that includes the set of encoded retrievaldata slices and the other set of DSN retrieval data addresses 356; andoutputs the yet another set of write slice requests that includes theset of encoded retrieval data slices (ERDS) 1-n of generation 3 to theset of DST execution units 1-n of the storage generation 3.

FIG. 40C illustrates initial steps of the example of the retrieving ofthe stored data to reproduce the data 352, where the inbound DSTprocessing 82 receives a read request regarding the data, where the readrequest includes the data name 354. Having received the data name 354,the inbound DST processing 82 estimates likely retrieval data storageinformation. Alternatively, the slice name module 350 estimates thelikely retrieval data storage information.

As a specific example, the slice name module 350 determines a logicalDSN address to physical storage device mapping (e.g., identifies DSNaddress ranges corresponding to each current storage generation). Asanother specific example, the slice name module 350 determineshistorical use patterns of the DSN memory (e.g., which storagegenerations hold the most retrieval data). As yet another specificexample, the slice name module 350 determines historical storagepatterns of a requesting entity that is requesting the read request(e.g., identify likely storage generations associated with storage ofretrieval data associated with the requesting entity).

Having estimated the likely retrieval data storage information, theslice name module 350 generates likely DSN retrieval data addresses 358based on the data name 354 and the likely retrieval data storageinformation. As a specific example, the slice name module 350 generatesthe likely DSN retrieval data addresses 358 to include generation 3 whenthe likely retrieval data storage information includes identification ofstorage generation 3.

With the likely DSN retrieval data addresses 358 being generated, theinbound DST processing 82 sends read requests to the likely DSNretrieval data addresses 358. As a specific example, the inbound DSTprocessing 82 sends, via the network 24, retrieval data read requestsfor generation 3, that includes a set of read slice requests 1-n, to theset of DST execution units associated with storage generation 3. The setof DST execution units 1-n issues read slice responses to the inboundDST processing 82, where the read slice responses includes encodedretrieval data slices of generation 3.

When favorable responses to the read requests have been received, theinbound DST processing 82 reconstructs the retrieval data. Havingreconstructed the retrieval data, the inbound DST processing 82 utilizesthe retrieval data to reconstruct the data. The reconstruction of thedata is discussed in greater detail with reference to FIG. 40D.

When the favorable responses to the read requests have not been received(e.g., if the read requests were sent to storage generation 4 instead of3), at least one of the inbound DST processing 82 and the slice namemodule 350 estimates a second likely retrieval data storage informationand generates second likely DSN retrieval data addresses based on thedata name and the second likely retrieval data storage information. Forexample, the slice name module 350 generates second likely DSN retrievaldata addresses for generation 3. Having generated the second likely DSNretrieval data addresses, the inbound DST processing 82 sends secondread requests to the second likely DSN retrieval data addresses. Forexample, the inbound DST processing 82 sends, via the network 24,retrieval data read requests for generation 3 to the set of DSTexecution units associated with storage generation 3. When favorableresponses to the second read requests have been received, the inboundDST processing 82 reconstructs the retrieval data and utilizes theretrieval data to reconstruct the data.

Alternatively, or in addition to, at least one of the inbound DSTprocessing 82 and the slice name module 350 determines to recover theretrieval data from at least two storage generations. The determiningincludes at least one of interpreting a request, interpreting anothersystem registry entry, and detecting that a system loading level is lessthan a system loading threshold level. When recovering from the at leasttwo storage generations, at least one of the inbound DST processing 82and the slice name module 350 estimates the second likely retrieval datastorage information. With the second likely retrieval data storageinformation, the slice name module 350 generates the second likely DSNretrieval data addresses based on the data name 354 and the secondlikely retrieval data storage information. With the second likely DSNretrieval data addresses, the inbound DST processing 82 sends, via thenetwork 24, the second read requests to the second likely DSN retrievaldata addresses. When favorable responses to either of the read requestsor the second read requests have been received, the inbound DSTprocessing 82 reconstructs the retrieval data and utilizes the retrievaldata to reconstruct the data.

FIG. 40D illustrates final steps of the example of the retrieving of thestored data to reproduce the data 352, where the inbound DST processing82 extracts the DSN data addresses from the reconstructed retrieval dataand issues data retrieval requests to the DSTN module 22 in accordancewith the extracted DSN data addresses. As a specific example, theinbound DST processing 82 generates a set of read slice requests thatincludes the plurality of sets of DSN data addresses based on theextracted DSN data addresses. Having generated the set of read slicerequests, the inbound DST processing 82 sends the set of read slicerequests to the set of DST execution units 1-n of storage generation 3,where the read slice requests includes read slice requests for theplurality of encoded data slices stored in storage generation 3. The setof DST execution units 1-n of storage generation 3 sends encoded dataslices of generation 3 to the inbound DST processing 82. The inbound DSTprocessing 82 decodes received encoded data slices to reproduce the data352.

FIG. 40E is a flowchart illustrating an example of accessing data. Themethod includes storage where at step 360 a processing module (e.g., ofa distributed storage and task (DST) client module of a dispersedstorage network (DSN)) sends a plurality of sets of encoded data slicesto DSN memory for storage in accordance with a plurality of sets of DSNdata addresses. The data was dispersed storage error encoded to producethe plurality of sets of encoded data slices. The data has a data nameand the plurality of sets of DSN data addresses is generated based on adata object number associated with the data and data storageinformation. The data name includes file system information. Theprocessing module may utilize a pseudo random number generator toproduce the data object number. The processing module may determine, asthe data storage information, dispersed storage error encodingparameters.

The method continues at step 362 where the processing module generatesretrieval data that is based on the data object number and the datastorage information. For example, the processing module generates theretrieval data to include a source name associated with the sets of DSNdata addresses. The method continues at step 364 where the processingmodule dispersed storage error encodes the retrieval data to produce aset of encoded retrieval data slices.

The method continues at step 366 where the processing module generates aset of DSN retrieval data addresses based on the data name and onretrieval data storage information. For example, the processing moduleperforms a deterministic function on the data name to produce aretrieval data object number. The processing module may determine, asthe retrieval data storage information, dispersed storage error encodingparameters. The method continues at step 368 where the processing modulesends the set of encoded retrieval data slices to the DSN memory forstorage therein in accordance with the set of DSN retrieval dataaddresses.

The processing module may facilitate storage of multiple copies of theset of encoded retrieval data slices. The method continues at step 370where the processing module determines to store multiple copies of theset of encoded retrieval data slices. The method continues at step 372where the processing module identifies multiple sets of storage units ofthe DSN memory for storing the multiple copies. The multiple sets ofstorage units being part of a logical storage vault within the DSNmemory, where a first set of storage units of the set of storage unitscorresponds to a first generation of the DSN memory and a second set ofstorage units of the set of storage units corresponds to a secondgeneration of the DSN memory.

For each copy of the multiple copies, the method continues at step 374where the processing module stores the multiple copies in the identifiedmultiple sets of storage units. For example, the processing modulegenerates a unique set of DSN retrieval data addresses based on the dataname, on the retrieval data storage information, and on a correspondingone of the multiple sets of storage units. Next, the processing modulesends the set of encoded retrieval data slices to the corresponding oneof the multiple sets of storage units for storage therein in accordancewith the unique set of DSN retrieval data addresses.

When retrieving the data, the method includes step 376 where theprocessing module receives a read request regarding the data, where theread request includes the data name. The method continues at step 378where the processing module estimates likely retrieval data storageinformation (e.g., estimates most probable generations). The estimatingthe likely retrieval data storage information includes one or more ofdetermining a logical DSN address to physical storage device mapping,determining historical use patterns of the DSN memory, and determininghistorical storage patterns of a requesting entity that is requestingthe read request.

The method continues at step 380 where the processing module generateslikely DSN retrieval data addresses based on the data name and thelikely retrieval data storage information. The method continues at step382 where the processing module sends read requests to the likely

DSN retrieval data addresses. The processing module may receiveresponses to the read requests. When favorable write responses to theread requests have been received, the method branches to step 390. Whenthe favorable responses to the read requests have not been received, themethod continues to step 384.

The method continues at step 384 where the processing module estimatessecond likely retrieval data storage information when the favorableresponses to the read requests have not been received. The methodcontinues at step 386 where the processing module generates secondlikely DSN retrieval data addresses based on the data name and thesecond likely retrieval data storage information. The method continuesat step 388 where the processing module sends second read requests tothe second likely DSN retrieval data addresses. When the favorableresponses to the read requests or second read requests have beenreceived, the method continues at step 390 where the processing modulereconstructs the retrieval data and utilizes the retrieval data toreconstruct the data.

Alternatively, or in addition to, the processing module may attempt torecover the retrieval data from multiple potential storage locations. Asa specific example, the processing module estimates the second likelyretrieval data storage information and generates the second likely DSNretrieval data addresses based on the data name and the second likelyretrieval data storage information. The processing module sends thesecond read requests to the second likely DSN retrieval data addresses.When the favorable responses to either of the read requests or thesecond read requests have been received, the processing modulereconstructs the retrieval data and utilizes the retrieval data toreconstruct the data.

FIG. 41 is a flowchart illustrating an example of updating a dispersedstorage network (DSN) address. The method includes step 400 where aprocessing module (e.g., of a distributed storage and task (DST)processing unit) determines to adjust a number of generations associatedwith a data object stored in a dispersed storage network (DSN). Thedetermining may include at least one of determining to add a generationwhen an amount of data associated with the data is growing anddetermining to delete a generation when the amount of data associatedwith the data a shrinking.

The method continues at step 402 where the processing module identifiesa number of generations associated with the data. The identifyingincludes looking up a current number of generations associated with thedata for a write request and estimating a number of generations thatexisted when the data was written when the access is the read request.The method continues at step 404 where the processing module generates ageneration number based on the number of generations. The generatingincludes performing a deterministic function on the data identifier andthe number of generations to produce the generation number. For example,the processing module obtains at least a portion (e.g., a vaultidentifier (ID) field entry, an object number field entry) of adispersed storage network (DSN) address associated with the data,performs a deterministic function on the portion of the DSN address toproduce a source name reference, and taking the source name referencemodulo number of generations to produce the generation number.

The method continues at step 406 where the processing module generates aDSN address using the generation number and based on the data. Forexample, the processing module utilizes the generation number in ageneration field of the DSN address, obtains a data ID, performs aregistry lookup to identify the vault ID for a vault ID field of the DSNaddress based on an accessing entity ID, and obtains an object numberfor an object number field of the DSN address associated with the dataID (e.g., look up in a directory or a dispersed hierarchical index;generate as a random number when writing the data). The method continuesat step 408 where the processing module identifies a set of storageunits based on the DSN address. The identifying includes at least one ofperforming a DSN address-to-physical address table lookup using the DSNaddress, initiating a query, and performing a generation-to-storage settable lookup using the generation number.

The method continues at step 410 where the processing module accessesthe set of storage units using the DSN address to retrieve a pluralityof sets of encoded data slices associated with the data. For example,the processing module generates and sends a plurality of sets of readslice requests to the set of storage units and receive a plurality of atleast a decode threshold number of read slice responses for each of thesets of read slice requests. The method continues at step 412 where theprocessing module identifies an updated number of generations associatedwith the data. The identifying includes adding or subtracting ageneration based on one or more of a volume of stored data trend, arequest, receiving an error message, and detecting a new set of storageunits. For example, the processing module determines to add a newgeneration when detecting the new set of storage units. As anotherexample, the processing module determines to delete a generation whendetecting that a current volume of stored data is less than a low storedata threshold level.

The method continues at step 414 where the processing module generatesan updated generation number based on the updated number of generations.For example, the processing module performs a deterministic function ona data identifier and the updated number of generations to produce theupdated generation number. The method continues at step 416 where theprocessing module generates an updated DSN address using the updatedgeneration number and based on the data. The generating includes atleast one of obtaining a data identifier, performing a lookup based on avault identifier, obtaining an object number, and performing a lookup.The lookup may include one or more of accessing a registry, accessing adirectory, and accessing a dispersed hierarchical index. The methodcontinues at step 418 where the processing module identifies another setof storage units based on the updated DSN address. The identifyingincludes at least one of performing a lookup, initiating a query, andidentifying the other set of storage units based on the updatedgeneration number of the updated DSN address.

The method continues at step 420 where the processing module accessesthe other set of storage units using the updated DSN address to storethe plurality of sets of encoded data slices associated with the data.The accessing includes issuing one or more sets of write slice requeststo the other set of storage units where the requests includes slicenames based on the updated DSN address. When the plurality of sets ofencoded data slices have been successfully stored, the method continuesat step 422 where the processing module deletes the plurality of sets ofencoded data slices from the set of storage units using the DSN address.The deleting includes issuing one or more sets of delete slice requeststo the set of storage units that includes slice names based on the DSNaddress.

FIG. 42 is a flowchart illustrating an example of accessing an encodeddata slice, which includes similar steps to FIG. 41. The method includesstep 424 where a processing module (e.g., of a distributed storage andtask (DST) execution unit) receives a read slice request that includes aslice name, where the slice name includes a generation number. Themethod continues at step 426 where the processing module determineswhether the generation number is associated with a locally storedencoded data slice. The determining may be based on accessing a localslice list. The method continues with step 402 of FIG. 41 where theprocessing module identifies a number of generations associated with thedata.

The method continues at step 428 where the processing module generatesan alternate generation number based on the generation number and thenumber of generations. The processing module may increment or decrementthe generation number based on a comparison of another generation numberthat is associated with locally stored encoded data slices and perform adeterministic function on the data identifier and the number ofgenerations. The method continues at step 430 where the processingmodule generates an alternate slice name using the alternate generationnumber and the slice name. The generating includes replacing thegeneration number with the alternate generation number in the slice nameto produce the alternate slice name.

The method continues at step 432 where the processing module identifiesanother storage unit based on the alternate slice name. The identifyingincludes accessing a list of storage units associated with a set ofgeneration number is associated with the slice name. The methodcontinues at step 434 where the processing module retrieves an encodeddata slice from the other storage units using the alternate slice name.The retrieving includes issuing a read slice requests to the otherstorage unit, where the request includes the alternate slice name. Theprocessing module receives the encoded data slice from the other storageunit. The method continues at step 436 where the processing moduleoutputs the encoded data slice to a requesting entity. Alternatively, orin addition to, the processing module stores the encoded data slice in alocal memory and updates slice location information.

FIGS. 43A, 43C-F are schematic block diagrams of an embodiment of adispersed storage network (DSN) illustrating an example of time-basedstorage of data. The DSN includes the distributed storage and task (DST)client module 34 of FIG. 1, the network 24 of FIG. 1, and thedistributed storage and a DST execution (EX) unit set 438. The DSTexecution unit set 438 includes a set of DST execution units 1-5. EachDST execution unit may be implemented utilizing the DST execution unit36 of FIG. 1. Hereafter, the DST execution unit set 438 may be referredto interchangeably as one or more of DSN memory, a set of storage units,and a storage unit set; and the DST execution unit may be referred tointerchangeably as a storage unit.

The DST client module 34 includes the outbound DST processing 80 of FIG.3. The DST client module 34 may further include a dispersed storage (DS)module 441. The DS module 441 may be implemented utilizing a pluralityof processing modules. For instance, the plurality of processing modulesmay include the processing module 84 of FIG. 3. As a specific example,the plurality of processing module includes a first module, a secondmodule, a third module, and a fourth module. The first through fourthmodules may be utilized to implement the outbound DST processing 80. TheDSN functions to time-based store a large data object 442 in the DSTexecution unit set 438. The large data object 442 may include at leastone of a video file, a records file, a collection of images file adocumentation file, or any other data object that has a data object sizegreater than a size threshold level, where the size threshold level isassociated with a storage process that has a time to completion ofstorage that compares unfavorably to a potential change in availabilityof the DST execution unit set 438. For example, the availability of theDST execution unit set 438 may change during a time frame that the largedata object is being stored to the DST execution unit set 438.

FIG. 43A illustrates initial steps of an example of the storing of thelarge data object 442, where the outbound DST processing 80 receives thelarge data object 442. Having received the large data object 442, theoutbound DST processing 80 encodes the large data object 442 inaccordance with a dispersed storage error coding function to produce aplurality of sets of encoded data slices. As a specific example, theoutbound DST processing 80 generates encoded data slice sets 1-M as theplurality of sets of encoded data slices and temporarily stores theencoded data slice sets 1-M in a send queue 440.

Having cached the encoded data slice sets 1-M, the outbound DSTprocessing 80 obtains estimated future availability information forstorage units of the DSN. As a specific example, the outbound DSTprocessing 80 obtains availability information 444 from the DSTexecution unit set 438. The availability information 444 includes one ormore of an expected pattern of availability, expected start time of andavailability level transition, expected duration of a next availabilityperiod, a maintenance schedule, a historical availability record, and anindication of a pending software update. As a specific example, the setof DST execution units 1-5 send, via the network 24, availabilityinformation 1-5 as the availability information 444 to the outbound DSTprocessing 80. Having received the availability information 444, theoutbound DST processing 80 interprets the availability information 444to produce the estimated future availability information for the storageunits. The generation and utilization of the estimated futureavailability information is discussed in greater detail with referenceto FIG. 43B.

FIG. 43B is a timing diagram illustrating an example of generating atime-availability pattern. The timing diagram includes a mapping of theestimated future availability information 446 versus time 448 and to atime-availability pattern 450. As a specific example, the mapping of theestimated future availability information 446 versus time 444 indicatesthat DST execution unit 1 is expected to be available from a currenttime of t0 until a time of t2, unavailable from t2 to t8 due to ascheduled software update, and available again from t8 to t10. Theexample mapping also indicates that DST execution unit 2 is expected tobe available from t0 to t5, unavailable from t5 to t8 due to scheduledmaintenance, and available from t8 to t10. The example mapping alsoindicates that DST execution unit 3 is expected to be available from t0to t6 and unavailable from t6 to t10 due to a scheduled power shutdown.The example mapping also indicates that DST execution units 4 and 5 areexpected to be available from t0 to t10.

Having obtained the estimated future availability information 446, theoutbound DST processing 80 of FIG. 43A organizes the plurality of setsof encoded data slices into a plurality of group-sets of encoded dataslices, where a group-set of encoded data slices includes multiple setsof encoded data slices. As a specific example, the outbound DSTprocessing 80 organizes encoded slice sets 1 through M1 (e.g., ofencoded slice sets 1-M) into a first group-set of encoded data slices tobe associated with a first write transaction, encoded slice sets M1+1through M2 into a second group-set of encoded data slices to beassociated with a second write transaction, encoded slice sets M2+1through M3 into a third group-set of encoded data slices to beassociated with a third write transaction, and encoded slice sets M3+1through M into a fourth group-set of encoded data slices to beassociated with a fourth write transaction.

For each of the plurality of group-set of encoded data slices, theoutbound DST processing 80 estimates an approximate storage completiontime to produce a plurality of approximate storage completion times. Theestimating of the approximate storage completion time may be based onone or more of a network performance level of the network 24, a loadinglevel for the DST execution unit set 438, a previous write transaction,a number of encoded data slices of the group-set of encoded data slices,and a size of each of the encoded data slices. As a specific example,the outbound DST processing 80 estimates that the first group-set ofencoded data slices has an approximate storage completion time of a timeduration associated with a time from t0 to t2.

Having estimated the approximate storage completion times, the outboundDST processing 80 obtains a write threshold number. The write thresholdnumber includes a minimum number of available storage units of the setof storage units to facilitate favorable write transactions of each ofthe group-sets of encoded data slices. The write threshold number isgreater than or equal to a decode threshold number and is less than orequal to an information dispersal algorithm (IDA) width, where thedecode threshold number and IDA width are associated with the dispersedstorage error coding function. The IDA width includes a number ofencoded data slices of each set of encoded data slices and the decodethreshold number includes a minimum number of encoded data slicesrequired to recover data associated with a set of encoded data slices.

Having obtained the write threshold number, the outbound DST processing80 establishes the time-availability pattern 450 for writing theplurality of group-sets of encoded data slices to the storage unitsbased on the estimated future availability information, the plurality ofapproximate storage completion times, and the write threshold number.The time-availability pattern 450 includes a plurality of time intervalsand an availability indication for each of the storage units in eachtime interval of the plurality of time intervals. The storing of agroup-set of the plurality of group-sets of encoded data slices spans atleast one time interval of the plurality of time intervals.

As a specific example of the time-availability pattern 450, the outboundDST processing 80 establishes the time-availability pattern 450 toinclude writing the first group-set of encoded data slices during timeinterval t0-t2 when all five storage units are expected to be available,writing the second group-set of encoded data slices during time intervalt2-t5 when four of the five storage units are available and the writethreshold number is three, writing the third group-set of encoded dataslices during time interval t5-t6 when three of the five storage unitsare available and the write threshold number is three, performing nowriting during time interval t6-t8 when less than the write thresholdnumber of storage units are expected to be available, and writing thefourth-set of encoded data slices during time interval t8-t10 when fourof the five storage units are expected to be available and the writethreshold number is three.

The time-availability pattern 450 may further include an indication tosend or withhold particular encoded data slices of a given set ofencoded data slices based on the estimated future availabilityinformation 446. As a specific example, the outbound DST processing 80determines to withhold sending encoded data slices to DST execution unit1 during the timeframe t2-t5 associated with the second writetransaction when DST execution unit 1 is expected to be unavailable. Forinstance, the outbound DST processing 80 holds encoded data slicesassociated with DST execution unit 1 in the send queue 440 during timeinterval t2-t8 and sends the held encoded data slices (e.g., unwrittenencoded data slices from the second and third write transactions) to theDST execution unit 1 over the time interval t8-t10.

FIG. 43C illustrates further steps of an example of the storing of thelarge data object 442, where the outbound DST processing 80 sends theplurality of group-sets of encoded data slices to at least some of thestorage units for storage in accordance with the time-availabilitypattern 450. The sending includes, for each of the plurality ofgroup-set of encoded data slices, the outbound DST processing 80assigning a transaction number (e.g., transaction numbers 1-4 for thefour group-sets of encoded data slices) and generating a write requestfor each available storage unit per the time-availability pattern 450 toproduce a set of write requests, where each write request of the set ofwrite requests includes the transaction number. As a specific example,the outbound DST processing 80 initiates a write transaction 1 at timet0. For instance, the outbound DST processing 80 sends, via the network24, a set of write slice requests 1-1 through 1-5 to DST execution units1-5, where the set of write slice request includes the first group-setof encoded data slices and the transaction number 1.

When, sending a given group-set of the plurality of group-sets ofencoded data slices, one of the storage units was listed as unavailable,the outbound DST processing 80 queues sending an encoded data slice ofeach set of the given group-set of encoded data slices and when the oneof the storage units is available and when another given group-set ofthe plurality of group-sets of encoded data slices is being sent to thestorage units, the outbound DST processing 80 sends the encoded dataslice of each set of the given group-set of encoded data slices to theone of the storage units.

FIG. 43D illustrates further steps of an example of the storing of thelarge data object 442, where the outbound DST processing 80 compares, astime passes, actual availability information of the storage units withcorresponding time portions of the estimated future availabilityinformation 446. As a specific example, the outbound DST processing 80re-obtains the availability information 444 from the DST execution unitset 438 prior to time t2. When the actual availability information doesnot substantially match the estimated future availability information446 for the corresponding time portions, the outbound DST processing 80adjusts the time-availability pattern 450 based on a difference betweenthe actual availability information and estimated future availabilityinformation for the corresponding time portions. For instance, theoutbound DST processing 80 suspends sending of a next group-set ofencoded data slices when the actual availability information for a nexttime frame indicates that less than the write threshold number ofstorage units are estimated to be available.

Alternatively, or in addition to, when, during the sending a givengroup-set of the plurality of group-sets of encoded data slices, lessthan the write threshold number of storage units are available, theoutbound DST processing 80 ceases the sending of the given group-set ofthe plurality of group-sets of encoded data slices and queues the givengroup-set of the plurality of group-sets of encoded data slices forsending to the at least some of the storage units when at least thewrite threshold number of storage units are available.

FIG. 43E illustrates further steps of an example of the storing of thelarge data object 442, where the outbound DST processing 80 initiates awrite transaction 2 at time t2. For instance, the outbound DSTprocessing 80 sends, via the network 24, a set of write slice requests2-1 through 2-5 to DST execution units 1-5, where the set of write slicerequest includes the second group-set of encoded data slices and thetransaction number 2.

FIG. 43F illustrates further steps of an example of the storing of thelarge data object 442, where the outbound DST processing 80 comparesfurther actual availability information of the storage units withcorresponding time portions of the estimated future availabilityinformation 446. As a specific example, the outbound DST processing 80re-obtains the availability information 444 from the DST execution unitset 438 prior to time t5 and interprets the re-obtained availabilityinformation 444 to produce the further actual availability information.When the further actual availability information does not substantiallymatch the estimated future availability information 446 for thecorresponding time portions, the outbound DST processing 80 adjusts thetime-availability pattern 450 based on a difference between the furtheractual availability information and estimated future availabilityinformation for the corresponding time portions.

FIG. 43G is a flowchart illustrating an example of time-based storage ofdata. In particular a method is presented for use in conjunction withone or more functions and features described in conjunction with FIGS.1-39 and also FIGS. 43A-F. The method includes step 460 where aprocessing module (e.g., of a distributed storage and task (DST) clientmodule of a dispersed storage network (DSN)) obtains estimated futureavailability information for storage units of the DSN. For example, theprocessing module receives the estimated future availability informationfrom the storage units.

The method continues at step 462 where the processing module organizes aplurality of sets of encoded data slices into a plurality of group-setsof encoded data slices. A group-set of encoded data slices includesmultiple sets of encoded data slices. The data is encoded in accordancewith a dispersed storage error coding function to produce the pluralityof sets of encoded data slices. Dispersal parameters are associated withthe dispersed storage error coding function. The dispersal parametersincludes one or more of an information dispersal algorithm width (e.g.,a number of encoded data slices of each set of encoded data slices), awrite threshold number (e.g., a subset number of the IDA width requiredto successfully write a representation of the set of encoded data slicesto the storage units), and a decode threshold number (e.g., a minimumnumber of encoded data slices of the set of encoded data slices requiredto recover data represented by the set of encoded data slices).

For each of the plurality of group-sets of encoded data slices, themethod continues at step 464 where the processing module estimates anapproximate storage completion time to produce a plurality ofapproximate storage completion times. The method continues at step 466where the processing module obtains the write threshold number (e.g.,retrieves from system registry information, receives, determines basedon storage requirements and a system performance level).

The method continues at step 468 where the processing module establishesa time-availability pattern for writing the plurality of group-sets ofencoded data slices to the storage units based on the estimated futureavailability information, the plurality of approximate storagecompletion times, and the write threshold number. The establishing mayinclude comparing, as time passes, actual availability information ofthe storage units with corresponding time portions of the estimatedfuture availability information and when the actual availabilityinformation does not substantially match the estimated futureavailability information for the corresponding time portions, adjustingthe time-availability pattern based on a difference between the actualavailability information and estimated future availability informationfor the corresponding time portions.

The method continues at step 470 where the processing module sends theplurality of group-sets of encoded data slices to at least some of thestorage units for storage in accordance with the time-availabilitypattern. The sending includes, for each of the plurality of group-setsof encoded data slices, assigning a transaction number and generating awrite request for each available storage unit per the time-availabilitypattern to produce a set of write requests, where each write request ofthe set of write requests includes the transaction number.Alternatively, or in addition to, when, for the sending of a givengroup-set of the plurality of group-sets of encoded data slices, one ofthe storage units was listed as unavailable, the processing modulequeues sending an encoded data slice of each set of the given group-setof encoded data slices. When the one of the storage units is availableand when another given group-set of the plurality of group-sets ofencoded data slices is being sent to the storage units, the processingmodule sends the encoded data slice of each set of the given group-setof encoded data slices to the one of the storage units.

Alternatively, or in addition to, when, during the sending a givengroup-set of the plurality of group-sets of encoded data slices, lessthan the write threshold number of storage units are available, theprocessing module ceases the sending of the given group-set of theplurality of group-sets of encoded data slices and queues the givengroup-set of the plurality of group-sets of encoded data slices forsending to the at least some of the storage units when at least thewrite threshold number of storage units are available.

FIG. 44A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit 36 of FIG. 11. The DSTexecution unit 36 includes an interface 169, the memory 88, thecontroller 86, a plurality of distributed task (DT) execution modules90, and a plurality of DST client modules 34. In an example ofoperation, the controller 86 obtains status of the plurality of DTexecution modules 90 and the plurality of DST client modules 34. Theobtaining includes one or more of issuing a task control message 480 tothe plurality of DT execution modules 90, issuing a DST control message482 to the plurality of DST client modules 34, receiving a task controlmessage 480 from one or more of the DT execution modules 90 thatincludes the status, and receiving a DST control message 482 from one ormore of the DST client modules 34 that includes the status. The statusincludes one or more of processing utilization level information, memoryutilization level information, garbage collection logs, errorinformation, and pending activity information.

In an example of operation, the controller 86 receives a request via theinterface 169, where the request includes at least one of a sliceprocessing request and a partial task 98. The controller 86 identifies aresource type based on the request (e.g., a DT execution module type forthe partial task 98 and a DST client module type for the sliceprocessing request). The controller 86 determines whether the resourcetype is available based on the status. When the resource type isavailable, the controller 86 selects a particular resource forassignment of the request. For example, the controller 86 identifies athird DST client module 34 that is most available for the request whenthe request is the slice processing request. As another example, thecontroller 86 selects a fourth DT execution module 90 when the fourth DTexecution module 90 is associated with processing resources capable ofexecuting the partial task 98 when the request is the partial task 98.The controller 86 assigns the request to the selected resource. Theassigning includes at least one of outputting an assignment task controlmessage to an assigned DT execution module 90 and outputting anassignment DST control message to the assigned DST client module. Whenthe resource type is not available, the controller 86 may issue an errorresponse via the interface 169 to a requesting entity and/or to amanaging unit.

The assigned DT execution module 90 executes the assigned partial task98 to produce partial results 102. Alternatively, or in addition to, theassigned DT execution module 90 facilitates the memory 88 to retrieveslices 96 and to output results 104. The assigned DST client module 34executes the slice processing request to facilitate producing at leastone of sub-slice groupings 170 and sub-partial partial tasks 172.Alternatively, or in addition to, the DST client module 34 mayfacilitate the memory 88 to provide slices 100 and/or two receivesslices 96 for further slice processing.

FIG. 44B is a flowchart illustrating an example of assigning resources.The method includes step 484 where a processing module (e.g., of acontroller module) obtains resource status information for a pluralityof task execution modules and a plurality of dispersed storage modules.The obtaining includes at least one of receiving, issuing a query,performing a lookup, accessing a historical record, and interpreting anactivity log. The method continues at step 486 where the processingmodule receives a request. The method continues at step 488 where theprocessing module identifies a resource type based on the request. Forexample, the processing module identifies the resource type based on atype of the request. For instance, the processing module identifies adistributed task execution module receiving a partial task requests. Inanother instance, the processing module identifies a distributed storageand task client module type when receiving a slice processing request.The processing module may identify another resource type for anotherrequest type.

The method continues at step 490 where the processing module determineswhether the resource type is available. For example, for each resource,the processing module interprets pending request to produce a predictedloading level and compares the predicted loading level to an upperloading level threshold. The processing module indicates availabilitywhen the comparison is favorable (e.g., more capacities available thanrequired). The method branches to step 494 when the resource type isavailable. The method continues to step 492 when the resource type isnot available. The method continues at step 492 where the processingmodule issues an error response when the resource type is not available.The issuing of the error response includes generating an error messageand sending the error message to at least one of a requesting entity anda managing unit.

The method continues at step 494 where the processing module selects atleast one resource of the plurality of task execution modules and theplurality of dispersed storage modules when the resource type isavailable. For example, the processing module identifies a resourceassociated with a most favorable comparison of predicted loading toavailable loading (e.g., most available capacity). The method continuesat step 496 where the processing module assigns the request to theselected at least one resource. For example, the processing module sendsthe request to the selected resource.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system that includes the distributedstorage and task network (DSTN) module 22 of FIG. 1, a set ofdistributed storage and task (DST) processing units 1-N, where each DSTprocessing unit includes the DST processing unit 16 of FIG. 1, and aload-balancing module 498. The DSTN module 22 includes the DST executionunit set 438 of FIG. 43A. The DST execution unit set 438 includes a setof DST execution units 36 of FIG. 1.

The system functions to store data 500 as a plurality of sets of encodeddata slices 504 in the DST execution unit set 438. The load-balancingmodule 498 selects one of the DST processing units, based on resourcestatus information 502 from the DST processing units, to encode the data500 using a dispersed storage error coding function to produce theplurality of sets of encoded data slices 504 for storage in the DSTexecution unit set 438. The resource status information 502 includes oneor more of an indicator of a time frame of availability, an indicator ofa time frame of unavailability, a time frame for a scheduled softwareupdate, a time frame for a scheduled new hardware addition, an errormessage, a maintenance schedule, a communications error rate, and astorage error rate.

In an example of operation, a DST processing unit determines to at leasttemporarily suspend operations. The determining may be based on one ormore of adding new software, activating new hardware, recovering from astorage error, recovering from a communications error, receiving asuspend request, and interpreting the maintenance schedule. The DSTprocessing unit continues to perform a slice access activity withregards to pending data access requests associated with the DSTprocessing unit. The load-balancing module 498 receives a new dataaccess request. The load-balancing module 498 determines availability ofeach of the DST processing units based on one or more of receivingresource status information 502, initiating a query, receiving an errormessage, and detecting an unfavorable performance (e.g., detecting slowresponse latency). The load-balancing module 498 selects the DSTprocessing unit when the availability (e.g., previously knownavailability) of the DST processing unit compares favorably toavailability of other DST processing units. The load-balancing module498 forwards the data access requests to the DST processing unit.

While suspending operations, the DST processing units indicates theunfavorable performance to the load-balancing module. The indicatingunfavorable performance includes at least one of ignoring the request,sending a late unfavorable response, issuing unfavorable resource statusinformation, and ignoring resource status requests from theload-balancing module. The load-balancing module 498 interprets theindication to determine that the data access request is to bereassigned. The load-balancing module 498 un-selects the DST processingunit from the data access assignment. For example, the load-balancingmodule sends a cancellation message to the DST processing unit andselects another DST processing unit and sends the data access request tothe other DST processing unit.

FIG. 45B is a diagram illustrating an example of load-balancing. Themethod includes step 506 where a distributed storage and task (DST)processing unit determines to temporarily suspend operations. The methodcontinues at step 508 where the DST processing unit continues to executepending operations. For example, the DST processing unit continues toprocess previously accepted data access requests. The method continuesat step 510 where a load-balancing module receives a data accessrequest. The method continues at step 512 where the load-balancingmodule assesses availability of a set of DST processing units thatincludes the DST processing unit. The assessing includes producingavailability information based on one or more of interpretingperformance indicators, receiving resource status information,initiating a query, receiving an error message, and detecting favorableperformance.

The method continues at step 514 where the load-balancing module selectsthe DST processing unit for execution of the data access request. Forexample, the load-balancing module selects the DST processing unit whenavailability of the DST processing unit compares more favorably toavailability of other DST processing units. The method continues at step516 where the load-balancing module forwards the data access request tothe DST processing unit.

The method continues at step 518 where the DST processing unit indicatesunfavorable performance. For example, the DST processing unit ignoresthe data access requests. As another example, the DST processing unitwaits a delay time period before sending a data access response causingthe load-balancing module to interpret the data access response as alate data access response associated with unfavorable performance. Asyet another example, the DST processing unit delays responses associatedwith previous accepted data access requests. The method continues atstep 520 where the load-balancing module detects the indicatedunfavorable performance. For example, the load-balancing module detectsthe indicated unfavorable performance when the data access response wasnot received within a desired response timeframe.

The method continues at step 522 where the load-balancing moduleun-selects the DST processing unit for execution of the data accessrequest. The un-selecting includes one or more of sending a cancellationmessage to the DST processing unit, selecting another DST processingunit for the data access request, and assigning the other DST processingunit the data access request.

The method continues at step 524 where the DST processing unitdetermines to resume operations. The determining may be based on one ormore of detecting that new software is operational, detecting that newhardware is operational, detecting that an error condition has cleared,and detecting that a level of pending data access requests has fallenbelow a low data access request threshold level. The method continues atstep 526 where the DST processing unit indicates favorable performance.For example, the DST processing unit generates data access responses inaccordance with desired data access response timing. As another example,the DST processing unit responds to all data access requests. As yetanother example, the DST processing unit sends favorable resource statusinformation to the load-balancing module.

FIG. 46A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit 36 that includes thedistributed storage and task (DST) client module 34 and one or morememory devices 88 of FIG. 3. The memory 88 includes a plurality ofportions of memory associated with different utilizations. The portionsmay be physical memory or virtual memory space. The plurality ofportions includes one or more portions utilized for slices memory 606,utilized for rebuilt slices memory 608, reserved for rebuilt slicesmemory 610, and un-utilized memory 612. The un-utilized memory 612 isassociated with available storage capacity, where the available storagecapacity may be calculated as a memory size minus memory used for eachof the utilized for slices memory 606, memory used for the utilized forrebuilt slices memory 608, and memory used for the reserved for rebuiltslices memory 610.

The DST execution unit 36 functions to store encoded data slices 600 inthe utilized for slices memory 606 and store rebuilt encoded data slices602 in the utilized for rebuilt slices memory 608. The DST client module34 may obtain the rebuilt encoded data slices by at least one of:receiving the rebuilt encoded data slices and generating the rebuiltencoded data slices by retrieving representations of encoded data slicesfrom a decode threshold number of other DST execution units 36. Whenencoded data slices are to be stored, the DST client module 34determines whether sufficient available storage capacity of theun-utilized memory is available for utilization for slices memory. Forinstance, the DST client module compares a size of an encoded data slicefor storage to the size of the un-utilized memory. The DST client moduleindicates that storage space is available when the size of the encodeddata slice is less than the size of the un-utilized memory. The DSTclient module 34 may determine the size of the reserved for rebuiltslices memory based on identifying encoded data slices to be rebuilt.The identifying includes at least one of detecting a slice error andreceiving an indication of the slice error.

In an example of operation, the DST client module 34 identifies aplurality of encoded data slices requiring rebuilding. The DST clientmodule 34 determines an amount of reserve memory 610 required forstorage of rebuilt slices for the identified plurality of encoded dataslices requiring rebuilding. The determining may include exchangingmemory utilization information 604 with at least one other DST executionunit, where the exchanging includes receiving an amount of memoryrequired for an encoded data slice associated with, for example, a sliceerror. The DST client module 34 updates the memory utilizationinformation to include the amount of reserve memory required. The memoryutilization information includes one or more of size of the utilized forslices memory, size of the utilized for rebuilt slices memory, size ofthe reserved for rebuilt slices memory, and size of the un-utilizedmemory. The DST client module 34 outputs the memory utilizationinformation 604 to one or more of a DST processing unit, a managingunit, and a user device.

The DST client module 34 obtains rebuilt encoded data slices (e.g.,receives, generates) and stores the rebuilt encoded data slices in theutilized for rebuilt encoded data slices memory. Accordingly, the DSTclient module updates the reserved for rebuilt slices memory by asimilar memory size amount as storage of the rebuild encoded data slices(e.g., lowers size of reserved for rebuilt slices memory and raises sizefor utilized for rebuilt slices memory). The DST client module updatesthe memory utilization information and may output the updated memoryutilization information.

FIG. 46B-C are diagrams illustrating examples of memory utilization fora series of times frames, where each timeframe indicates an amount ofmemory utilized for slices, rebuilt slices, reserved for rebuilt slices,unutilized, and a total amount of memory capacity. The total amount ofmemory capacity remains constant over the time intervals. In particular,FIG. 46 B illustrates examples of the memory utilization 614 for a firstset of time intervals T1-5. At T1, stored slices use 300 TB of memoryspace of a total capacity of 500 TB of memory space leaving 200 TB ofunutilized memory space. At T2, 50 TB of slices for rebuilding aredetected such that reserved for rebuilding is incremented by 50 TB andunutilized memory space is lowered by 50 TB from 200 TB to 150 TB. AtT3, a first 20 TB of rebuilt slices are obtained and stored such thatthe reserved memory space for rebuilt slices is lowered by 20 TB from 50TB to 30 TB. At T4, a remaining 30 TB of rebuilt slices are obtained andstored such that the reserve memory space rebuilt slices is lowered byanother 30 TB from 30 TB two 0 TB and the rebuilt slices is raised tobuy 30 TB from 20 TB to 50 TB. At T5, the rebuilt slices are moved tothe memory space for slices thus raising the rebuilt slices by 50 TBfrom 300 TB to 350 TB. Utilized memory includes the combination 615 ofutilized for slices memory 606, memory used for the utilized for rebuiltslices memory 608, and memory used for the reserved for rebuilt slicesmemory 610.

FIG. 46C continues the examples of memory utilization 616 for second setof time intervals T6-T10. The example begins at time interval T6 whichis equivalent to memory utilization of T5. At T7, 100 TB of new slicesare stored thus raising the memory utilization of slices from 350 TB to450 TB and lowering the unutilized memory space from 150 TB to 50 TB. AtT8, 50 TB of slices for rebuilding is detected such that memory space ofreserved for rebuilding is incremented by 50 TB from zero to 50 TB andmemory space of unutilized is lowered by 50 TB from 50 TB two 0 TB.Requests for storage of new slices are rejected since the memory spaceof the unutilized memory is zero. At T9, 50 TB of rebuilt slices arereceived and stored in the memory space of the rebuilt slices thusraising the rebuilt slices from 0 TB to 50 TB and lowering the memoryspace for rebuilt slices from 50 TB to 0 TB. At T10, the slices of thememory space rebuilt slices is considered part of the memory space ofslices thus raising the memory space of the slices from 450 TB to 500 TBand lowering the memory space of the rebuilt slices from 50 TB to 0 TB.As such, the memory storage space is full and subsequent request forstorage of slices or rebuilt slices shall be rejected.

FIG. 46D is a flowchart illustrating an example of updating memoryutilization information. The method begins at step 618 where aprocessing module (e.g., of a distributed storage and task (DST) clientmodule) identifies a plurality of encoded data slices requiringrebuilding. As further delineated in FIG. 46E (flowchart illustratingexample ways to identify slices needing a rebuild), the identifyingincludes at least one of: receiving an error message 632 (e.g., noslices detected for rebuild, no access to rebuild information, notenough space to rebuild, etc.); receiving a rebuilding request 634(e.g., to rebuild specific data slices or range of data slices);detecting missing or corrupted encoded data slices by comparing a listof locally stored encoded data slices (or range of slices) to a list ofremotely stored encoded data slices (or range of slices) associated withthe locally stored encoded data slices to identify missing slices ordetecting unfavorable slice integrity (e.g., corrupted slices);monitoring downloads 638 to the DS memory meeting minimum read/write(R/W) width thresholds but less than a full pillar width (successfuldownload, but not all slices above threshold successfully downloaded);determining 640 when DSN read/write (R/W) requests occur for theplurality of encoded data slices and comparing to known times ofinaccessibility for the DS memory storing the plurality of encoded dataslices (e.g., DS memory was down for maintenance when original slice R/Wrequest occurred); and querying vaults related to the plurality ofencoded data slices 641 to determine one or more missing or corruptedencoded data slices (e.g., other vaults sharing the same data slices mayhave a list or copies which include the missing or corrupted dataslices).

The rebuilding of the plurality of encoded data slices is, in oneembodiment, queued for at least one of individual, group, or batchprocessing and the processing will be performed at a significant timedelay from the queuing. As the rebuild processing may occur in thefuture, the embodiments of FIGS. 46A-G, ensure that memory space is setaside for rebuilds such that interceding requests for memory slicestorage will not over utilize memory needed for the rebuild before ithas a chance to occur.

The method continues at the step 620 where the processing moduledetermines an amount of memory space to reserve for the plurality ofencoded data slices requiring rebuilding. The determining includesidentifying slice sizes based on at least one of initiating a slice sizequery with regards to the remotely stored encoded data slices, receivinga query response, and performing a local lookup based on a slice name.

The method continues at step 622 where the processing module updatesmemory utilization information to include the amount of memory space toreserve. For example, the processing module increments an amount ofmemory reserved for rebuilt slices by the amount of memory space toreserve and decrements unutilized memory space by the amount of memoryspace to reserve. The method continues at step 624 where the processingmodule sends the memory utilization information to at least one of astoring entity and a managing unit. The sending may further includedetermining whether a sum of an amount of memory utilized for slices, anamount of memory utilize for rebuilt slices, and an amount of memoryreserved for rebuilt slices is greater than a capacity of memory. Whenthe sum is greater, the processing module may further send an indicationthat the memory is full.

The method continues at step 626 where the processing module obtainsrebuilt encoded data slices (e.g., received, generate). The methodcontinues at step 628 where the processing module stores the rebuiltencoded data slices in a local DS memory. The method continues at step630 where the processing module updates the amount of memory space toreserve for remaining encoded data slices requiring rebuilding. Theupdating includes determining an amount of memory space utilized tostore the obtained rebuilt encoded data slices, incrementing the amountof memory space utilized for rebuilt slices by the amount of memoryspace utilized to store the obtained rebuilt encoded data slices, anddecrementing the amount of memory space reserved for rebuilt slices bythe amount of memory space utilized to store the obtained rebuiltencoded data slices. The updating may further include updating thememory space utilized for slices to include the amount of memory spaceutilized to store the obtained rebuilt encoded data slices anddecrementing the amount of memory space utilized to store the rebuildencoded data slices. The method loops back to the step where theprocessing module updates the memory utilization information.

FIG. 46F is a flowchart illustrating another example of updating memoryutilization information. The method begins at step 642 where aprocessing module (e.g., DST integrity processing unit 20) attempts toretrieve a plurality of encoded data slices from a DS memory to performan integrity check. Slices are retrieved based on any of: list(s) ofslice addresses, list(s) of names, range(s) of slice addresses andrange(s) of slice names. In step 644, it is determined if the encodeddata slices were retrieved during the attempted retrieval. In step 646,for encoded data slices that were not received and/or not listed, theyare flagged as missing slices. For retrieved encoded data slices, theyare checked for errors due to data corruption, outdated version, etc. Instep 648, if a slice includes an error, it is flagged as a ‘bad’ slice.Bad and/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices.

The rebuilding of the plurality of encoded data slices is, in oneembodiment, queued for at least one of individual, group, or batchprocessing and the processing will be performed at a significant timedelay from the queuing. As the rebuild processing may occur in thefuture, the embodiments of FIGS. 47A-G, ensure that memory space is setaside for rebuilds such that interceding requests for memory slicestorage will not over utilize memory needed for the rebuild before ithas a chance to occur.

The method continues at the step 650 where the processing moduledetermines an amount of memory space to reserve for the plurality ofencoded data slices requiring rebuilding. The determining includesidentifying slice sizes based on at least one of initiating a slice sizequery with regards to the remotely stored encoded data slices, receivinga query response, and performing a local lookup based on a slice name.

The method continues at step 652 where the processing module updatesmemory utilization information to include the amount of memory space toreserve. For example, the processing module increments an amount ofmemory reserved for rebuilt slices by the amount of memory space toreserve and decrements unutilized memory space by the amount of memoryspace to reserve. The method continues at step 653 where the processingmodule sends the memory utilization information to at least one of astoring entity (e.g., storage/vault peers), user units and a managingunit. The sending may further include determining whether a sum of anamount of memory utilized for slices, an amount of memory utilize forrebuilt slices, and an amount of memory reserved for rebuilt slices isgreater than a capacity of memory. When the sum is greater, theprocessing module may further send an indication that the memory isfull.

The method continues at step 654 where the processing module obtainsrebuilt encoded data slices (e.g., received, generated) and stores, instep 656, the rebuilt encoded data slices in a local DS memory. Themethod continues at step 657 where the processing module updates theamount of memory space to reserve for remaining encoded data slicesrequiring rebuilding. The updating includes determining an amount ofmemory space utilized to store the obtained rebuilt encoded data slices,incrementing the amount of memory space utilized for rebuilt slices bythe amount of memory space utilized to store the obtained rebuiltencoded data slices, and decrementing the amount of memory spacereserved for rebuilt slices by the amount of memory space utilized tostore the obtained rebuilt encoded data slices. The updating may furtherinclude updating the memory space utilized for slices to include theamount of memory space utilized to store the obtained rebuilt encodeddata slices and decrementing the amount of memory space utilized tostore the rebuild encoded data slices.

FIG. 46G is a schematic block diagram illustrating an example DST clientmodule 34 structure for memory utilization. DST client module 34 mayinclude a plurality of processing modules (or sub-modules) to performone or more steps of the embodiments of FIGS. 46A-F. While this exampleis shown as seven separate modules, the modules may becombined/separated into any number of modules (local or remote) tocomplete the various steps and functions of the various embodiments ofFIGS. 46A-F.

As shown, identify module 34-1 identifies a plurality of encoded dataslices that require rebuilding, wherein rebuilding of the plurality ofencoded data slices is queued for at least one of individual, group, orbatch processing and the processing will be performed at a significanttime delay from the queuing. Determine module 34-2 determines an amountof memory required for storage of the rebuild encoded data slices forthe plurality of encoded data slices. Update module 34-3 updatesutilization information of the memory by allocating a portion ofavailable memory to the amount of memory required. Indicate module 34-4indicates the memory utilization (e.g., by sending the updatedutilization information 604 of the memory to at least one of a storingentity (e.g., other storage/vault peers) and a managing unit). Obtainmodule 34-5 obtains rebuilt data slices (e.g., from other good copies orrelated vaults or generates them from other encoded data slices). Storemodule 34-6 stores the rebuilt encoded data slices in the reservememory; and modify module 34-7 modifies the utilization information toreflect the stored rebuilt encoded data slices. Additional modules maybe included within DST client module 34 to perform additional tasks (forexample, but not limited to, passing encoded data slices to/from slicememory during non-rebuild write/read (W/R) operations). Alternatively,obtain module 34-5 and store module 34-6 may perform the receive andstore slices 600 tasks, respectively.

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system that includes the disbursingstorage and task (DST) processing unit 16 and the distributed storageand task network (DSTN) module 22 of FIG. 1. The DSTN module 22 includesat least two DST execution unit sets 1-2. Each DST execution unit setincludes a set of DST execution units 36 of FIG. 1. The system functionsto store at least two data objects in a common DST execution unit set.

In an example of operation, the DST processing unit 16 receives a dataobject 1 write request 700. The DST processing unit 16 encodes dataobject 1 using a dispersed storage error coding function to producefirst sets (data object 1) of encoded data slices 700-1, 2, . . . n(where n equals the width (number of pillars) of the encoded data sliceset). The DST processing unit 16 generates first sets of slice names forthe first sets of encoded data slices. The DST processing unit 16 issuesone or more sets of data object 1 write slice requests to a DSTexecution unit set 1 that includes the first sets of encoded data slicesand the corresponding first sets of slice names, where the first sets ofslice names fall within a range of slice names associated with the DSTexecution unit set 1.

With data object 1 stored in the first set of DST execution units 36,the DST processing unit 16 receives a data object 2 co-locate writerequest 702 with regards to storing a second data object in the same setof DST execution units 36 as the first data object (e.g., in the DSTexecution unit set 1). The data object 2 co-locate write requestincludes a data identifier (ID) of the data object to be co-located with(e.g., a data ID of the data object 1), a data ID of the second dataobject (e.g., the data object 2 to be co-located), and may include thedata (e.g., data object 2) to be co-located when it is not alreadystored within the DSTN module 22.

When the data object to be co-located (e.g., the second data object) isincluded in the data object 2 co-locate write request, the DSTprocessing unit 16 identifies the set of DST execution units 36associated with the data ID of data object 1 to be co-located with(e.g., the DST execution unit set 1). The determining includes accessingone or more of a directory and a dispersed hierarchical index toidentify a DSN address associated with the data ID of data object 1 tobe co-located with and performing a DSN address-to-physical locationtable lookup to identify the set of DST execution units 36 associatedwith the data ID of data object 1 to be co-located with. Next, the DSTprocessing unit encodes the second data object (data object 2) toproduce second sets of encoded data slices for storage in the DSTexecution unit set 1. The DST processing unit 16 generates second setsof slice names for the second sets of encoded data slices, where thesecond sets of slice names are based on the first sets of slice namessuch that the second sets of slice names fall within a range of slicenames associated with a range of slice names associated with the set ofDST execution units 36 associated with the data ID of data object 1 tobe co-located with. DST processing unit 16 issues data object 2 writeslice requests to the set of DST execution units 36 associated with thedata ID of the data object to be co-located with (e.g., to DST executionunit set 1), where the data object 2 write slice requests includes thesecond sets of encoded data slices.

When the data object to be co-located is not included in the data object2 co-locate write request, the DST processing unit 16 determines whetherthe data object to be co-located is already co-located. The determiningincludes the DST processing unit 16 identifying the DST execution unitset associated with storage of the second data object and comparing theidentity to the identity of the DST execution unit set associated withstorage of the first data object. When data object 2 to be co-located isnot already co-located (e.g., with data object 1), the DST processingunit 16 recovers data object 2 from the DST execution unit setassociated with storage of the second data object (e.g., from DSTexecution unit set 2). The recovering includes issuing data object 2read slice requests 704 to the DST execution unit set associated withstorage of the second data object and receiving the second sets ofencoded data slices (e.g., received from DST execution unit set 2).Next, the DST processing unit 16 issues the data object 2 write slicerequests to the set of DST execution units 36 associated with the dataID of the data object 1 to be co-located with (e.g., to DST executionunit set 1), where the data object 2 write slice requests includes thereceived second sets of encoded data slices and the corresponding secondsets of slice names.

FIG. 47B is a diagram illustrating an example of generating an updatedslice name for a previously stored encoded data slice of a second dataobject to be co-located with one or more encoded data slices of a firstdata object. The slice name 706 has a structure that includes a sliceindex field 708, a vault identifier (ID) field 710, a generation field712, an object number field 714, and a segment number field 716. Asubstantial number of the fields of the slice name structure of a slicename of the previously stored encoded data slice of the second dataobject are updated to be substantially aligned with corresponding fieldsof the slice name structure of a slice name of the one or more encodeddata slices of the first data object. For example, a vault ID fieldentry of the previous data object 2 slice 1 is updated to besubstantially the same as a vault ID field entry of data object 1 slice1. As another example, an object number field entry of the previous dataobject 2 slice 1 is updated based on an object number field entry of theprevious data object 2 slice 1 such that the slice name of the updateddata object 2 slice 1 falls within a range of slice names associatedwith storage of the first data object.

FIG. 47C is a flowchart illustrating an example of co-locating storageof data objects. The method begins at step 718 where a processing module(e.g., a distributed storage and task (DST) processing unit) receives adata object 2 co-locate write request to co-locate a data object 2 witha data object 1 to be co-located with. The write request includes one ormore of data identifiers (IDs) for the data object 2 to be co-locatedand the data object 1 to be co-located with. The method continues atstep 720 where the processing module obtains a plurality of sets ofencoded data slices for the data object 2 to co-locate. The obtainingincludes one of receiving, generating, and retrieving. When receiving,the processing module extracts the plurality of sets of encoded dataslices from the write request 700. When generating, the processingmodule encodes the data object 2 to be co-located using a dispersedstorage error coding function to produce the plurality of sets ofencoded data slices. When retrieving, the processing module identifiesprevious sets of slice names utilized to store the plurality of sets ofencoded data slices based on a data ID of the data object 2 to becomeco-located, issues one or more sets of read slice requests to apreviously utilized set of storage units where the one or more sets ofread slice requests includes the previous sets of slice names, andreceiving the plurality of sets of encoded data slices 704.

The method continues at the step 722 where the processing modulegenerates a plurality of sets of slice names for the plurality of setsof encoded data slices based on addressing information of the dataobject 1 to be co-located with. For example, the processing modulegenerates the plurality of sets of slice names to include a vault IDassociated with the data object to be co-located with and an objectnumber field entry that causes the generated plurality of sets of slicenames to fall within a slice name range that is associated with a set ofstorage units where the data object to be co-located with is stored.

The method continues at the step 724 where the processing module storesthe plurality of sets of encoded data slices in the set of storage unitsusing the generated plurality of sets of slice names. The storingincludes generating one or more sets of write slice requests thatincludes the plurality of sets of encoded data slices and the generatedplurality of sets of slice names and outputting the one or more sets ofread slice requests to the set of storage units. When storage of theplurality of sets of encoded data slices in the set of storage units isconfirmed, and when the plurality of sets of encoded data slices wereretrieved using the previous sets of slice names, the method continuesat the step 726 where the processing module deletes the plurality ofsets of encoded data slices utilizing the previous sets of slice names.For example, the processing module issues a set of delete slice requeststhat includes the previous sets of slice names to the previous utilizedset of storage units.

FIG. 47D is a flowchart illustrating one example of obtaining theplurality of sets of encoded data slices to be co-located. Theobtaining, step 720, includes multiple processing paths for receiving,generating, and retrieving the plurality of sets of encoded data slicesto be co-located (data object 2) based on the location of data object 2at the time of the request. When receiving, the processing moduleextracts in step 727 the ID of data object 1, ID of data object 2 and,if included with the request, the plurality of data object 2 sets ofencoded slices from the write request 700. When data object 2 to beco-located (e.g., the second data object) is included in the data object2 co-locate write request, the DST processing unit 16 identifies,beginning with step 730, the set of DST execution units 36 associatedwith data ID 1 of the data object to be co-located with (e.g., the DSTexecution unit set 1). The determining includes accessing one or more ofa directory in step 731 and a dispersed hierarchical index in step 732to identify a DSN address associated with data object 1 ID to beco-located with and performing a DSN address-to-physical location tablelookup in step 734 to identify the physical location (PL) address set ofDST execution units 36 associated with the data ID of the data object tobe co-located with. If data object 2 is not already encoded, it isencoded in step 729 using a dispersed storage error coding function.

When the data object to be co-located is not included in the data object2 co-locate write request, the DST processing unit 16 determines whetherthe data object to be co-located is already co-located. The determiningincludes comparing data object 2 PL to data object 1 PL. If they areco-located (data object 2 PL is stored within a range of addresses fordata object 1 PL) no further action is required. When data object 2 tobe co-located is not already co-located, the DST processing unit 16recovers (reads), in step 736, the second data object from the DSTexecution unit set associated with storage of the second data object(e.g., from DST execution unit set 2).

FIG. 47E is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentdisclosure. DST processing unit 16 may include a plurality of processingmodules (or sub-modules) to perform one or more steps of the embodimentsof FIGS. 47A-D. While this example is shown as four separate modules,the modules may be combined or separated into any number of modules(local or remote) to complete the various steps and functions of thevarious embodiments of FIGS. 47A-D.

As shown, receive module 16-1 operates to receive a data objectco-locate write request. Obtain module 16-2 operates to obtain aplurality of sets of encoded data slices for a data object to co-locate.Generate module 16-3 operates to generate a plurality of sets of slicenames for the data object to co-locate based on another plurality ofsets of slice names associated with a data object to be co-located with.Store module 16-4 operates to store the plurality of sets of encodeddata slices in DS memory using the generated plurality of sets of slicenames for the data object co-locate.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present disclosure has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed disclosure. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed disclosure. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present disclosure may have also been described, at least in part,in terms of one or more embodiments. An embodiment of the presentdisclosure is used herein to illustrate the present disclosure, anaspect thereof, a feature thereof, a concept thereof, and/or an examplethereof. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process that embodies the presentdisclosure may include one or more of the aspects, features, concepts,examples, etc. described with reference to one or more of theembodiments discussed herein. Further, from figure to figure, theembodiments may incorporate the same or similarly named functions,steps, modules, etc. that may use the same or different referencenumbers and, as such, the functions, steps, modules, etc. may be thesame or similar functions, steps, modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors. Unless specifically stated to the contra,signals to, from, and/or between elements in a figure of any of thefigures presented herein may be analog or digital, continuous time ordiscrete time, and single-ended or differential. For instance, if asignal path is shown as a single-ended path, it also represents adifferential signal path. Similarly, if a signal path is shown as adifferential path, it also represents a single-ended signal path. Whileone or more particular architectures are described herein, otherarchitectures can likewise be implemented that use one or more databuses not expressly shown, direct connectivity between elements, and/orindirect coupling between other elements as recognized by one of averageskill in the art.

The term “module” is used in the description of the various embodimentsof the present disclosure. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules. While particular combinations of variousfunctions and features of the present disclosure have been expresslydescribed herein, other combinations of these features and functions arelikewise possible. The present disclosure is not limited by theparticular examples disclosed herein and expressly incorporates theseother combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: obtaining estimated future availabilityinformation for storage units of the DSN; organizing a plurality of setsof encoded data slices into a plurality of group-sets of encoded dataslices, wherein a group-set of encoded data slices of the plurality ofgroup-sets of encoded data slices includes multiple sets of encoded dataslices of the plurality of sets of encoded data slices, wherein data isencoded in accordance with a dispersed storage error coding function toproduce the plurality of sets of encoded data slices; for each of theplurality of group-sets of encoded data slices, estimating anapproximate storage completion time to produce a plurality ofapproximate storage completion times; obtaining a write thresholdnumber; establishing a time-availability pattern for writing theplurality of group-sets of encoded data slices to the storage unitsbased on the estimated future availability information, the plurality ofapproximate storage completion times, and the write threshold number;and sending the plurality of group-sets of encoded data slices to atleast some of the storage units for storage therein in accordance withthe time-availability pattern.
 2. The method of claim 1 furthercomprises: comparing, as time passes, actual availability information ofthe storage units with corresponding time portions of the estimatedfuture availability information; and when the actual availabilityinformation does not substantially match the estimated futureavailability information for the corresponding time portions, adjustingthe time-availability pattern based on a difference between the actualavailability information and estimated future availability informationfor the corresponding time portions.
 3. The method of claim 1 furthercomprises: for each of the plurality of group-sets of encoded dataslices, assigning a transaction number; and wherein the sending theplurality of group-sets of encoded data slices to at least some of thestorage units for storage therein in accordance with thetime-availability pattern includes: generating a write request for eachavailable storage unit per the time-availability pattern to produce aset of write requests, wherein each write request of the set of writerequests includes the transaction number.
 4. The method of claim 1,wherein the time-availability pattern comprises: a plurality of timeintervals, wherein storing a group-set of the plurality of group-sets ofencoded data slices spans at least one time interval of the plurality oftime intervals; and an availability indication for each of the storageunits in each time interval of the plurality of time intervals.
 5. Themethod of claim 1 further comprises: when, for the sending of a givengroup-set of the plurality of group-sets of encoded data slices, one ofthe storage units was listed as unavailable, queuing sending an encodeddata slice of each set of the given group-set of encoded data slices;and when the one of the storage units is available and when anothergiven group-set of the plurality of group-sets of encoded data slices isbeing sent to the storage units, sending the encoded data slice of eachset of the given group-set of encoded data slices to the one of thestorage units.
 6. The method of claim 1 further comprises: when, duringthe sending a given group-set of the plurality of group-sets of encodeddata slices, less than the write threshold number of storage units areavailable: ceasing the sending of the given group-set of the pluralityof group-sets of encoded data slices; and queuing the given group-set ofthe plurality of group-sets of encoded data slices for sending to the atleast some of the storage units when at least the write threshold numberof storage units are available.
 7. A dispersed storage (DS) module of adispersed storage network (DSN), the DS module comprises: a firstmodule, when operable within a computing device, causes the computingdevice to: obtain estimated future availability information for storageunits of the DSN; a second module, when operable within the computingdevice, causes the computing device to: organize a plurality of sets ofencoded data slices into a plurality of group-sets of encoded dataslices, wherein a group-set of encoded data slices of the plurality ofgroup-sets of encoded data slices includes multiple sets of encoded dataslices of the plurality of sets of encoded data slices, wherein data isencoded in accordance with a dispersed storage error coding function toproduce the plurality of sets of encoded data slices; a third module,when operable within the computing device, causes the computing deviceto: for each of the plurality of group-sets of encoded data slices,estimate an approximate storage completion time to produce a pluralityof approximate storage completion times; obtain a write thresholdnumber; and establish a time-availability pattern for writing theplurality of group-sets of encoded data slices to the storage unitsbased on the estimated future availability information, the plurality ofapproximate storage completion times, and the write threshold number;and a fourth module, when operable within the computing device, causesthe computing device to: send the plurality of group-sets of encodeddata slices to at least some of the storage units for storage therein inaccordance with the time-availability pattern.
 8. The DS module of claim7 further comprises: the third module, when operable within thecomputing device, further causes the computing device to: compare, astime passes, actual availability information of the storage units withcorresponding time portions of the estimated future availabilityinformation; and when the actual availability information does notsubstantially match the estimated future availability information forthe corresponding time portions, adjust the time-availability patternbased on a difference between the actual availability information andestimated future availability information for the corresponding timeportions.
 9. The DS module of claim 7 further comprises: the fourthmodule, when operable within the computing device, further causes thecomputing device to: for each of the plurality of group-sets of encodeddata slices, assign a transaction number; and wherein the fourth modulefunctions to cause the computing device to send the plurality ofgroup-sets of encoded data slices to at least some of the storage unitsfor storage therein in accordance with the time-availability pattern by:generating a write request for each available storage unit per thetime-availability pattern to produce a set of write requests, whereineach write request of the set of write requests includes the transactionnumber.
 10. The DS module of claim 7, wherein the time-availabilitypattern comprises: a plurality of time intervals, wherein storing agroup-set of the plurality of group-sets of encoded data slices spans atleast one time interval of the plurality of time intervals; and anavailability indication for each of the storage units in each timeinterval of the plurality of time intervals.
 11. The DS module of claim7 further comprises: the fourth module, when operable within thecomputing device, further causes the computing device to: when, for thesending of a given group-set of the plurality of group-sets of encodeddata slices, one of the storage units was listed as unavailable, queuesending an encoded data slice of each set of the given group-set ofencoded data slices; and when the one of the storage units is availableand when another given group-set of the plurality of group-sets ofencoded data slices is being sent to the storage units, send the encodeddata slice of each set of the given group-set of encoded data slices tothe one of the storage units.
 12. DS module of claim 7 furthercomprises: the fourth module, when operable within the computing device,further causes the computing device to: when, during the sending a givengroup-set of the plurality of group-sets of encoded data slices, lessthan the write threshold number of storage units are available: ceasethe sending of the given group-set of the plurality of group-sets ofencoded data slices; and queue the given group-set of the plurality ofgroup-sets of encoded data slices for sending to the at least some ofthe storage units when at least the write threshold number of storageunits are available.